Why are Children in the Same Family So Different? Nonshared Environment a Decade Later
Bibliographic record
Abstract
OBJECTIVE: To review recent developments in the study of nonshared environment; that is, the environmental influences that make children growing up in the same family different, rather than similar. METHOD: We review several recent influential books and papers on the subject of nonshared environment from the decade following the 1987 paper that highlighted its importance in psychological development. RESULTS: Modest progress has been made toward identifying the specific aspects of the environment responsible for nonshared environment. Although parents treat their multiple children differently, such differential treatment accounts for only a small amount of nonshared environmental influence, once genetic factors are controlled. It has been suggested that some degree of nonshared environment may be due to the fact that siblings react differently to ostensibly shared environmental influences. Peer influence and other experiences outside the family may be more important sources of systematic nonshared environment. CONCLUSIONS: Despite the difficulties encountered in identifying specific sources of nonshared environment, the fact remains that most environmental variance affecting the development of psychological dimensions and psychiatric disorders is not shared by children growing up in the same family. More research and theory are needed to explain why such siblings are so different. Chance, in the sense of idiosyncratic experiences, also needs to be considered.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".